pyopia.instrument.holo

pyopia.instrument.holo#

This is a module containing basic processing for reconstruction of in-line holographic images with pyopia.pipeline.

See (and references therein): Davies EJ, Buscombe D, Graham GW & Nimmo-Smith WAM (2015) ‘Evaluating Unsupervised Methods to Size and Classify Suspended Particles Using Digital In-Line Holography’ Journal of Atmospheric and Oceanic Technology 32, (6) 1241-1256, https://doi.org/10.1175/JTECH-D-14-00157.1 https://journals.ametsoc.org/view/journals/atot/32/6/jtech-d-14-00157_1.xml

2022-11-01 Alex Nimmo-Smith alex.nimmo.smith@plymouth.ac.uk

Functions

clean_stack(im_stack, stack_clean)

clean the im_stack by removing low value pixels - set to 0 to disable

create_kernel(im, pixel_size, wavelength, n, ...)

create reconstruction kernel

find_focus_imax(im_stack, bbox, ...)

finds and returns the focussed image for the bbox region within im_stack using intensity of bbox area

find_focus_sobel(im_stack, bbox, ...)

finds and returns the focussed image for the bbox region within im_stack using edge magnitude of bbox area

forward_transform(im[, forward_filter_option])

Perform forward transform with optional filtering

generate_config(raw_files, model_path, ...)

Generaste example holo config.toml as a dict

inverse_transform(im_fft, kern, im_stack[, ...])

create the reconstructed hologram stack of real images

load_image(filename)

load a hologram image file from disc

max_map(im_stack)

_summary_

read_lisst_holo_info(filename)

reads the non-image information (timestamp, etc) from LISST-HOLO holograms

rescale_image(im)

rescale im (e.g.

std_map(im_stack)

_summary_

Classes

Focus([stacksummary_function, threshold, ...])

PyOpia pipline-compatible class for creating a focussed image from an image stack

Initial(wavelength, n, offset, minZ, maxZ, stepZ)

PyOpia pipline-compatible class for one-time setup of holograhic reconstruction

Load([prefix_chars])

PyOpia pipline-compatible class for loading a single holo image

MergeStats()

PyOpia pipline-compatible class for merging holo-specific statistics into output stats

Reconstruct([stack_clean, ...])

PyOpia pipline-compatible class for reconstructing a single holo image